generating-transcriptional-regulation-view-transcriptomic-features

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets

Transcriptome represents the expression levels of many genes in a sample and has been widely used in biological research and clinical practice. ...

Jilin University

The Forkhead box P3 (FOXP3) transcription factor is the key driver of the differentiation and immunosuppressive function of regulatory T cells (Tregs). Additionally, FOXP3 has been reported to be expressed in many solid tumor cell lines and tissues. However, its role in tumorigenesis and tumor progression is conflicting, both tumor suppressive and promoting functions have been described. In this study, we demonstrated that FOXP3 was expressed in both lung adenocarcinoma tissues and the lung adenocarcinoma cell line A549. FOXP3 inhibition decreased cell proliferation, migration, and invasion as well as the secretion of inhibitory cytokines (e.g., transforming growth factor beta 1 (TGF-β1), interleukin 35 (IL-35), and heme oxygenase-1 (HMOX1)), suggesting a positive role for FOXP3 in tumor development. Importantly, we found that FOXP3 could enhance lung adenocarcinoma cell proliferation via upregulating the levels of the cell cycle G1/S checkpoint gene CCND1. These data demonstrated that FOXP3 could be regarded as a novel therapeutic target for inhibiting lung adenocarcinoma progression.

Overexpression of the transcription factor FOXP3 in lung adenocarcinoma sustains malignant character by promoting G1/S transition gene CCND1.

Objective. Asthma is a chronic inflammatory disorder. Despite extensive researches into the treatment and management of it, current treatments and management strategies are still limited. The search for a novel approach to its treatments is urgently needed. Researches on the potential medical use of polyoxometalates (POMs) have already shown it has antiviral and antitumor bioactivities. But the effects of POM in immune systems are still largely unknown. Methods. In order to investigate the role of POM in the asthmatic disease, we used OVA-induced asthma murine model and observed the pathological changes between mice that received three different Ti-substituted POMs (0.3 μg per mouse per dose) when challenged with OVA. We also measured the type 2 cytokine expressions to reveal the potential mechanism. Results and Conclusions. Our results showed that two Ti-substituted POMs, K5H2[FeW11TiO40]·17H2O and K5H[H2ZnW11TiO40]·35H2O, could reduce OVA-induced lung inflammation, serum IgE level (around 2000 ng/mL to less than 1000 ng/mL), leukocytes infiltration in the lung, and cytokines levels (including IL-4, IL-5, IL-13, and TNF-α) but Ti-centered POM K4[TiW12O40]·10H2O did not. Thus, Ti-substituted POMs may have pharmaceutical values especially in treatments for asthmatic diseases.

A Novel Application of Ti-Substituted Polyoxometalates: Anti-Inflammatory Activity in OVA-Induced Asthma Murine Model.

Vitamin A (VA) deficiency is one of the most common malnutrition conditions. Recent reports showed that VA plays an important role in the immune balance; lack of VA could result in enhanced type 2 immune response characterized by increased type 2 cytokine production and type 2 innate lymphoid cell infiltration and activation. Type 2 immune response plays protective role in anti-infection but plays pathological role in asthmatic disease. In order to investigate the role of VA in the asthmatic disease, we used ovalbumin-induced asthma murine model and observed the pathological changes between mouse-received VA-deficient and VA-sufficient diets. We also measured the type 2 cytokine expressions to reveal the potential mechanism. Our results showed that VA deficiency exacerbates ovalbumin-induced lung inflammation and type 2 cytokine productions. Thus, VA deficiency, or malnutrition in further extent, may contribute to the increasing prevalence of asthma.

Vitamin A Deficiency Promotes Inflammation by Induction of Type 2 Cytokines in Experimental Ovalbumin-Induced Asthma Murine Model.

Multiple advanced logic circuits including the full-adder, full-subtract and majority logic gate have been successfully realized on a DNA/GO platform for the first time. All the logic gates were implemented in an enzyme-free condition. The investigation provides a wider field of vision towards prototypical DNA-based algebra logical operations and promotes the development of advanced logic circuits.

Integration of DNA and graphene oxide for the construction of various advanced logic circuits.

Toll-like receptor 4 (TLR4) is a pattern recognition receptors, a member of the Toll-like receptor family and it serves a role in innate and acquired immunity. It has previously been reported that TLR4 was overexpressed in a variety of tumor tissues and cells, including colorectal cancer, gastric cancer and ovarian cancer. In the tumor microenvironment, the TLR4 signaling pathway may be activated in order to upregulate forkhead box P3 (Foxp3) expression in regulatory T cells (Tregs), and thus enhance the immunosuppressive function of Tregs. Also, inflammatory cytokine release would be increased, which promotes tumor immune system evasion. Additionally, it has previously been reported that TLR4 activation may induce histone methylation changes at multiple sites. However, the effects of the alterations to histone methylation in the process of TLR4-associated tumor immune system evasion are not currently known. Histone methylation serves a critical role in regulating gene expression. Abnormal histone methylation is closely associated with tumor development and progression. In order to investigate the epigenetic mechanisms underlying Foxp3 regulation by TLR4, the human lung adenocarcinoma cell line A549 was used. In the present study, it was revealed that the expression level of H3K9me1/2 histone lysine demethylase 3A (KDM3A) was significantly increased following TLR 4 activation in the lung adenocarcinoma A549 cell line, whereas silencing of KDM3A expression led to significantly reduced Foxp3 expression under TLR4 regulation. This result suggests that KDM3A participates in TLR4 regulation of Foxp3 transcription. Additional analysis revealed that during nuclear transport of Foxp3, KDM3A may directly bind to the Foxp3 promoter and activate its transcription. This results in increased secretion of Foxp3-downstream inhibitory cytokines, including transforming growth factor-β1 (TGF-β1), interleukin 35 (IL-35) and heme oxygenase 1 (HO-1), which have immunosuppressive effects and ultimately facilitate the immune escape of lung cancer cells. From the results, the present study concluded that TLR4 activation promoted the expression of H3K9me1/2 demethylase KDM3A. KDM3A bound directly to the Foxp3 promoter and promoted Foxp3 transcription, thereby inducing the secretion of Foxp3-associated downstream inhibitory cytokines (TGF-β1, IL-35, and HO-1), ultimately facilitating the immune system evasion of lung adenocarcinoma.

KDM3A promotes inhibitory cytokines secretion by participating in TLR4 regulation of Foxp3 transcription in lung adenocarcinoma cells.

Smart homes are designed to promote safe and comfortable living for inhabitants without any manual intervention. The performance of approaches for daily activity recognition is therefore crucial, but current real-time approaches have to wait until a daily activity ends before performing recognition. We present an approach for timely daily activity recognition from an incomplete stream of sensor events, by which the recognition process can start as soon as a daily activity begins. Activity features are generated from several headmost sensor events rather than from all sensor events that a daily activity activated. A public dataset was utilized to evaluate the presented method. Experimental findings show its effectiveness for timely daily activity recognition in terms of precision, recall, average saved time, and saved time proportion.

Timely daily activity recognition from headmost sensor events.

Solar cells based on organic-inorganic hybrid halide perovskites (OIHHPs) have been widely studied because of their increasing power conversion efficiency. Extensive research has been conducted in electrical and optical properties and device fabrication. However, in terms of material science, the photovoltaic effects of OIHHP are still not well understood. Here, we theoretically investigate the photovoltaic phenomena of MAPbI (MA = CHNH) under standard AM 1.5G sunlight illumination, considering the MA cation orientation, light incident angle, polarization, and photon energy, using Keldysh nonequilibrium Green's function formalism combined with density functional theory calculations. It is found that the short-circuit current density  has a maximum value of 383.149 A/m when the MA orientation is parallel to the transport direction, whereas it is negligible when the MA orientation is orthogonal to the transport direction. In addition, full consideration is also given to the direction of incidence of sunlight and its polarization state. Nevertheless, of all factors considered, MA orientation plays the decisive role, for  still has a respectable value of 364.112 A/m even for a 90° sunlight incident angle relative to the transport direction, so long as the MAs are aligned in the transport direction. The increase in the photocurrent is attributed to an increase in the transmission coefficient of low-energy holes, as well as improvement of the velocities and mobilities of electrons and holes in the MAPbI-based device with [001] MA orientation. The results suggest that during the designing of high-performance OIHHP-based solar cells and photoelectronic devices, the crystal orientation and MA cation orientation relative to the transport direction should be carefully considered as they directly affect carrier transport properties.

Photovoltaic Effect Related to Methylammonium Cation Orientation and Carrier Transport Properties in High-Performance Perovskite Solar Cells.

MXene is recognized as an ideal material for sensitive wearable strain sensors because of its unique advantages of conductivity, hydrophilicity and mechanical properties. However, conventional hydrogel sensors utilizing MXene as a conductive material inevitably encounter the excessive accumulation of MXene nanosheets during the process of synthesis, which limits the electron transmission, reduces the conductivity, and concurrently weakens the mechanical capability and sensitivity of sensors. Herein, we construct a dispersion-enhanced MXene hydrogel (DEMH) through a chitosan-induced self-assembly strategy for the first time. Charge transfer is carried out through the flow of a material or a collection of material microstructures, and thus the highly interconnected 3D MXene@Chitosan network provides fast transport channels for electrons, and the DEMH exhibits excellent conductivity and sensibility simultaneously. Besides, the electrostatic self-assembly between MXene and chitosan, and the supramolecular interactions between MXene, chitosan and polyacrylamide chain segment result in excellent mechanical strength (of up to 1900%) and flexibility of DEMH. Furthermore, the introduction of chitosan which possesses a high density of positively charged groups and MXene with semiconducting properties also endows sensor versatility, such as self-adhesion properties and antibacterial activity. This work develops a simple and cut-price strategy for combining MXene unaggregated into a hydrogel as a sensor with high conductivity, sensibility and flexibility. A simple and inexpensive strategy for avoiding self-stacking of two-dimensional conductive materials is proposed, which paves the way for a broad range of applications in electronic skin, human motion detection and intelligent devices.

A conductive polyacrylamide hydrogel enabled by dispersion-enhanced MXene@chitosan assembly for highly stretchable and sensitive wearable skin.

Flexible strain sensors are attracting enormous attention due to their high stretchability and sensitivity that are required for wearable devices and electronic skin. However, diverse application environments require materials whose hardness can be adjusted to satisfy different demands. Herein, we developed a synergistic dual network hydrogel PANI-P(AAm--AA)@Fe composed of an iron-coordinated poly(acrylamide--acrylic acid) network and a conductive polyaniline network with adjustable mechanical properties and high sensitivity. Through controlling the degree of protonation, the cross-linking density will be changed and the mechanical properties of PANI-P(AAm--AA)@Fe can be regulated in a wide range (ultimate tensile stress: 0.0710-0.3054 MPa) (fracture strain: 145-880%). Besides, the host-guest interaction between β-cyclodextrin (β-CD) and polyaniline improves the compatibility of polyaniline in a hydrogel substance and leads to the formation of homogenous interpenetrating networks, which provide PANI-P(AAm--AA)@Fe with outstanding and steady conductivity (2.03-3.67 S m). Furthermore, PANI-P(AAm--AA)@Fe exhibits highly linear sensitivity, a wide working region (gauge factor = 0.48 at 0-400% strain) and excellent durability (300 cycles). A strain sensor based on this hydrogel can detect not only large movements such as bending fingers and wrists but also delicate movements such as swallowing and a pulse, indicating its enormous potential in wearable devices, human health monitoring, electronic skin, human-machine interactions and so on.

Fe-Coordination mediated synergistic dual-network conductive hydrogel as a sensitive and highly-stretchable strain sensor with adjustable mechanical properties.

Colon cancer is a common cancer type in both sexes and its mortality rate increases at the metastatic stage. Most studies exclude nondifferentially expressed genes from biomarker analysis of metastatic colon cancers. The motivation of this study is to find the latent associations of the nondifferentially expressed genes with metastatic colon cancers and to evaluate the gender specificity of such associations. This study formulates the expression level prediction of a gene as a regression model trained for primary colon cancers. The difference between a gene's predicted and original expression levels in a testing sample is defined as its mqTrans value (model-based quantitative measure of transcription regulation), which quantitatively measures the change of the gene's transcription regulation in this testing sample. We use the mqTrans analysis to detect the messenger RNA (mRNA) genes with nondifferential expression on their original expression levels but differentially expressed mqTrans values between primary and metastatic colon cancers. These genes are referred to as dark biomarkers of metastatic colon cancer. All dark biomarker genes were verified by two transcriptome profiling technologies, RNA-seq and microarray. The mqTrans analysis of a mixed cohort of both sexes could not recover gender-specific dark biomarkers. Most dark biomarkers overlap with long non-coding RNAs (lncRNAs), and these lncRNAs might have contributed their transcripts to calculating the dark biomarkers' expression levels. Therefore, mqTrans analysis serves as a complementary approach to identify dark biomarkers generally ignored by conventional studies, and it is essential to separate the female and male samples into two analysis experiments. The dataset and mqTrans analysis code are available at https://figshare.com/articles/dataset/22250536.

Gender-specific dysregulations of nondifferentially expressed biomarkers of metastatic colon cancer.

Coronavirus disease 2019 (COVID-19) is a rapidly developing and sometimes lethal pulmonary disease. Accurately predicting COVID-19 mortality will facilitate optimal patient treatment and medical resource deployment, but the clinical practice still needs to address it. Both complete blood counts and cytokine levels were observed to be modified by COVID-19 infection. This study aimed to use inexpensive and easily accessible complete blood counts to build an accurate COVID-19 mortality prediction model. The cytokine fluctuations reflect the inflammatory storm induced by COVID-19, but their levels are not as commonly accessible as complete blood counts. Therefore, this study explored the possibility of predicting cytokine levels based on complete blood counts.

Yaqing Liu

College of Computer Science and Technology,
and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,
College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education

Jilin University

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets

Yaqing Liu

College of Computer Science and Technology,and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education

Jilin University

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets

College of Computer Science and Technology,
and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,
College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education